Summary Statistics

Species Information

Visualization of ht vs focal 50

Correlation at each band

effect of height focal against visitation

##    Tree Height Month Year           Species   utm1  utm2 ele Visitation
## 16   79   high    10 2016 Oenocarpus bataua 644127 38676 540        189
##    Richness M.Richness B.Richness T.Ingestions T.Removal T.Nibble
## 16        5          0          5           57       117        0
##    Avg.synch.neighbors Lek. DAP_CENSUS_1 ALTURA_CENSUS_1 NOTAS_CENSUS_1
## 16                  NA LEK1         29.5              21             NA
##    TIPO_DE_BOSQUE_COLLECTION DOSEL_CENSUS_1 CANOPY_DENS_CENSUS_1
## 16                Secundario             21                91.42
##    ARB_DAP10_CENSUS_1 ARB_DAP50_CENSUS_1 CERCROPIA_CENSUS_1 MICONIA_CENSUS_1
## 16                  9                  0                  0                0
##    JUV_CENSUS_1 JUV_DENS_CENSUS_1 PLANTULA_CENSUS_1 PLANTULA_DENS_CENSUS_1
## 16            4        0.05092958                41               2.088113
##    m.visitation b.visitation real.visitation real.m.visitation
## 16            0          189             189                 0
##    real.b.visitation real.richness real.m.richness real.b.richness  date
## 16               189             5               0               5 42644
##    focalmonth..10 focalmonth..50 focalmonth..100 focalmonth..150
## 16              0              2               3               6
##    focalmonth..200 focalmonth..250 focalmonth..300 focalmonth..350
## 16               9              10              12              15
##    focalmonth..400 focalmonth..450 focalmonth..500 focalmonth..550
## 16              16              16              16              18
##    focalmonth..600 focalmonth..650 focalmonth..700 focalmonth..750
## 16              20              21              24              25
##    focalmonth..800 focalmonth..850 focalmonth..900 focalmonth..950 TD  FD NRFM
## 16              25              25              25              25  0 189    1
##    NFM NRFG NFG   start      end days vis.rate num.close  FD.rate TD.rate
## 16   d    1   e 10/5/16 10/16/16   11 17.18182         5 17.18182       0

Models 50 m band

Models using functional groups

Model Comparisons

Model 1: Original

## real.visitation ~ focalmonth..50 * Height + offset(lograte) + 
##     (1 + focalmonth..50 | Tree)
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.0405307 0.1886986 0.2147905 0.8299306
focalmonth..50 0.5152201 0.2956979 1.7423871 0.0814407
Heightlow 0.7238617 0.0437088 16.5610200 0.0000000
focalmonth..50:Heightlow -0.2752461 0.0374950 -7.3408839 0.0000000

Model 2: Trees without any visits from Dispersers are removed

## real.visitation ~ focalmonth..50 * Height + offset(lograte) + 
##     (1 + focalmonth..50 | Tree)
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.0415496 0.1880433 0.2209575 0.8251255
focalmonth..50 0.5152245 0.2960341 1.7404230 0.0817848
Heightlow 0.7235774 0.0436765 16.5667539 0.0000000
focalmonth..50:Heightlow -0.2750984 0.0374846 -7.3389674 0.0000000

Results are qualitatively similar.

Model 3: Original amount of trees, but fruiting neighborhood is now binary

## real.visitation ~ bin50 * Height + offset(lograte) + (1 + bin50 | 
##     Tree)
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.0439227 0.1998483 0.219780 0.8260425
bin501 0.5713877 0.3322725 1.719636 0.0854987
Heightlow 0.6624992 0.0483892 13.691042 0.0000000
bin501:Heightlow -0.3084512 0.0692597 -4.453547 0.0000084

Again, binarizing is qualitatively similar.

Model 4: Original amount of trees, but fruiting neighborhood categorized into 0,1,2,3+

## real.visitation ~ bin50 * Height + offset(lograte) + (1 + bin50 | 
##     Tree)
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.0276333 0.1891375 0.1461019 0.8838409
bin50 0.5471455 0.2952029 1.8534560 0.0638170
Heightlow 0.7421483 0.0450024 16.4913175 0.0000000
bin50:Heightlow -0.3186904 0.0420803 -7.5733801 0.0000000

Model 5: Original data but tree with outlier in visitation in high cameras removed

## real.visitation ~ focalmonth..50 * Height + offset(lograte) + 
##     (1 + focalmonth..50 | Tree)
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.0650785 0.1908849 0.3409307 0.7331558
focalmonth..50 0.3663191 0.3096886 1.1828626 0.2368636
Heightlow 0.6933769 0.0439534 15.7752735 0.0000000
focalmonth..50:Heightlow -0.0700859 0.0400875 -1.7483212 0.0804084

Focalmonth..50 and the interaction term are no longer significant.

Model 6: Trees without any visits from Dispersers are removed AND outlier in visitation in high cameras removed

## real.visitation ~ focalmonth..50 * Height + offset(lograte) + 
##     (1 + focalmonth..50 | Tree)
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.0657147 0.1905568 0.3448563 0.7302024
focalmonth..50 0.3664713 0.3096947 1.1833307 0.2366781
Heightlow 0.6931354 0.0439257 15.7797227 0.0000000
focalmonth..50:Heightlow -0.0699615 0.0400800 -1.7455466 0.0808898

Results are qualitatively similar again when trees with 0 disperser visitation is removed